scoringutils
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Utilities for Scoring and Assessing Predictions
Consider the following example: ``` df score(metrics = metrics_quantile(select = "wis")) ``` This just produces a normal output. `wis()` does have an argument `na.rm = TRUE`, so in theory all...
In the old version, we don't compute a log score for discrete sample-based forecasts. The reason for that is that the `scoringRules` implementation of the log score estimates a density,...
`get_forecast_unit()` currently relies on an internal call to `get_protected_columns()` to identify which columns it should ignore. These are currently things like `quantile_level` and `sample_id`. This all works well within the...
**Update**: Current plan is to: - write a helper function to check that - enforce it in `bias_quantile()` as it's needed there - check + warn in `validate_forecast()`. --- This...
I think the "Getting Started" vignette is well-written but quite long. May I suggest writing a simpler version of the current one and splitting the current one into smaller chunks,...
It would be nice to give the users code that exemplifies how they can visualise their scores and forecasts. We should also add an updated version of `plot_score_table()` which is...
In addition, should check that there aren't any function calls that aren't imported in a function. One example was ` dt
We should aim to increase our code coverage and bring it back up. ~Specifically, we should double-check the codecov report from #583 - codecov complained that a few lines were...
Currently, a few tests print messages and #583 adds more tests that do that. It would be nicer to have those tests not print anything ideally by - addressing the...
Result of repeated `devtools::test()` ```r `assert_input_interval(observed, lower, upper, 0.5)` did not throw the expected warning. ``` because the warning is only shown once by design.